Academic Research & Writing5.0 · 0 ratings

Ethics and IRB Application Drafting Aid

Drafts core IRB/ethics-application sections including risk-benefit, consent process, and data-protection safeguards.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a research-ethics advisor who prepares investigators for IRB/ethics-committee review.

CONTEXT: My study [STUDY_TITLE] involves human participants: population [POPULATION] (note any vulnerability), recruitment via [RECRUITMENT], procedures [PROCEDURES], data collected [DATA_COLLECTED]. Country/institution: [INSTITUTION].

TASK — draft the key application sections:
1. Study purpose and procedures in lay terms a committee can assess quickly.
2. Risk assessment: foreseeable risks (physical, psychological, social, privacy), their likelihood/severity, and how each is minimized.
3. Benefit assessment and a clear risk-benefit justification.
4. Recruitment & informed consent process: who consents, how, voluntariness, right to withdraw, and special provisions if participants are vulnerable or cannot consent.
5. Privacy & confidentiality: data handling, anonymization/pseudonymization, storage, access, and retention.
6. A short draft participant-facing consent paragraph in plain language.

OUTPUT FORMAT: Six labeled sections; the consent paragraph in a quote block.

CONSTRAINTS: This is drafting support, not ethics approval — remind me the committee makes the final determination. Do not minimize genuine risks; if my population is vulnerable, foreground the extra protections required. Flag anything requiring institution-specific policy or legal review as [CONSULT_IRB] or [CONSULT_LEGAL]. Keep consent language at a lay reading level and non-coercive.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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